The present invention relates to a moving picture coding method and apparatus using dynamic motion estimation for low bit-rate systems, and more particularly, to a moving picture coding method and apparatus for low bit-rate systems using dynamic motion estimation that estimates the motion and shape of an image and encodes generated parameters.
Recently, there has been much attention directed to digital moving picture transmission techniques for low bit-rate systems. The techniques can be applied to various video broadcasting systems, for example, video telephones, video conferencing equipment, industrial inspection cameras and network television systems. Specifically, there is a prospect that various video equipment operated at a transmission rate lower than 64 Kbps is connected to an integrated services digital network (ISDN), i.e., a digital transmission network. Therefore, a moving picture coding technique applicable to systems having a transmission rate lower than 64 Kbps is becoming significant.
As for a model suggested by a moving picture experts group (MPEG), 30 frames per second is processed at a relatively high bit-rate, for example, 1.5.about.10 Mbps. The basic algorithm used in the MPEG system is a combination of differential pulse code modulation and a transform coding method and is for all blocks having a fixed size. However, for the case of coding at low bit-rate, for example, lower than 64 Kbps, a greater video data compression is required due to the limitation of the transmission rate, as compared with the MPEG system.
The most significant operation in low bit-rate moving picture coding is the extraction of a parameter for effectively reproducing the current image based on the previous image. Thus, emphasis is placed on coding the analyzed content through motion analysis of the changed portion. In the past, the extraction of a brightness signal change component for each block was based on blocks having a fixed size or several fixed sizes. Here, the result was coded via a transform coding method. Recently, though, studies have concentrated on an object-oriented coding method where a moving object is extracted in accordance with the edges of the object or by changes in the pixels that constitute the object, and a parameter generated by a motion analysis of the object is coded.
As for a block matching method generally employed for motion estimation in a conventional moving picture coding technique, an image is divided into blocks having a predetermined size, and movement in the x and/or y axis directions is determined as a motion vector (x, y) when the sum of absolute error is most smallest while searching for a predetermined block of the current image within predetermined ranges of the previous image. However, such a motion estimation method is applied equally, including to the portion having no changes from the previous image. Thus, a long processing time is required and image quality is degraded. In addition, since the movement of an object is usually not in regular square block units, the correct motion cannot be estimated using conventional block matching.
Accordingly, block matching is a method for reducing the data being coded, by reducing the difference between a target image and a reference image, rather than a method for estimating the correct motion.
In order to partially solve the problems of the block matching method, the size of the unit block has been reduced. Further, there have been attempts to segment a large size object into sub-blocks and to generate the motion vector by estimation of motion in the x and y axis directions with respect to each sub-block. Here, the motion of each sub-block is sought independently. Therefore, there is a limit in reducing the size and number of objects for analysis. In addition, it is hard to introduce an additional dimension of motion, for example, rotation, in such method.
It should be noted that motion and an object for analysis in a moving picture image are closely related to each other. In other words, a motion estimation process seeks the motion with respect to the object, but the motion component greatly affects the extracting of an object for analysis.
In a moving picture coding technique, the conventional motion estimation technique is independent of the motion characteristic with respect to such analysis object, and fixes one component while estimating another using the fixed component so as to extract data. Thus, a large amount of duplication exists in the extracted data, and image quality is degraded due to imprecise processing.
Meanwhile, there have been efforts to apply mathematical means to the extracting of a motion component of the object for analysis. Relatively accurate motion estimation can be achieved by such mathematical analysis when the right object for analysis is selected. However, mathematical analysis is extremely complex and difficult to implement using hardware. In addition, the mathematical analysis technique establishes a motion estimation region prior to performing the motion estimation, which causes difficulties in performing motion estimation optimally.